WP2.2.2: Agricultural micro-Insurance, Tanzania

Maize, Tanzania

C. Gornott

Objectives

We will demonstrate how climate services can contribute to the implementation of nationwide micro-insurance schemes for smallholder farmers in Tanzania. In a nutshell, risk transfer instruments will enhance the ability of the farmers to adapt to climate change and altered weather patterns. Therefore, they are of general interest to farmers, traders (e.g. grain mills, retailers), rural banks, insurance companies, and last but not least to policymakers and government institutions.

A problem of large-scale application of insurance schemes is the validation of yield loss claims for a group of potential underwriters (indemnified farmers) in the region, often only remotely connected to road networks and information infrastructure. This requires an effective, quantifiable, and verifiable assessment of yield losses. By combining already established crop yield models with advanced and high-resolution remote sensing and climate re-analysis methodologies, we support insurers to better determine local yield loss claims and to better estimate their overall financial risk. In turn, such risk transfer instruments have a huge potential to stabilize smallholder farmers’ income and therefore to stimulate adoption of improved cultivation techniques, supporting agricultural development and counteracting malnutrition and large-scale food shortages (IPCC AR5 2015).

As in many regions in Sub-Saharan Africa, the share of labour in the agricultural sector done by woman is estimated between 50-80% in Tanzania (Worldbank, 2015). Insurances, which cover losses of smallholder crop production, address gender issues by indemnifying woman, which are more vulnerable to climate related production shocks.

Description

About 30 million people work in the agricultural sector in Tanzania, and as irrigation schemes are fairly underdeveloped, most of them are highly vulnerable to weather-related yield losses. This vulnerability might accelerate under climate change conditions. The financial uncertainty of the farmers inhibits implementation of improved and resilient farming systems and endangers food security. Therefore, our methodology, already tested at the plot, county and national scale, has the potential to hugely support agricultural development and can be a means to adapt to climate variability and change.

The work will build on an already established cooperation of PIK (crop yield modelling) and GAF AG (high-resolution remote sensing) with Munich Re for the determination of yield loss claims of smallholder farmers in Tanzania. It will be amended by high-resolution weather re-analysis modelling (TU Delft), adjusted to weather information of the Trans-African Hydro-Meteorological Observatory network (TAHMO), and the actuarial evaluation will be done by Munich Re.

First results have already been provided for Tanzania at the county scale and for selected plots, using national statistics and field surveys as information for validation. This was done using a combination of statistical and dynamical crop yield models to distinguish weather and management impacts (Gornott and Wechsung 2016, Conradt et al. 2016). The step to be done now is to provide the results for the local scale for entire Tanzania.

The fine scale information to do so will be high-resolution satellite and weather model data. The assimilation of these data in the crop model chain has already been tested at the plot scale and will be extended to all regions in Tanzania, following the OASIS LMF standard for risk estimation.The applied methodology is unique in that it allows distinguishing between yield losses attributable to unfavourable weather pattern (which are covered by insurance) and due to agronomic management (which is uncovered by insurance); a major demand of the insurance partners, making it superior to pure weather related indexes.

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This project has received funding from the European Union's Horizon 2020 research and innovation programme
European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme
Euratom research and training programme 2014-2018 under grant agreement No H2020_Insurance 730381